5cbd3f29e3
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73 lines
2.0 KiB
C++
73 lines
2.0 KiB
C++
// Copyright (c) ONNX Project Contributors
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//
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// SPDX-License-Identifier: Apache-2.0
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#include <memory>
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#include <string>
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#include "gtest/gtest.h"
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#include "onnx/common/ir.h"
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#include "onnx/common/ir_pb_converter.h"
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namespace ONNX_NAMESPACE {
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namespace Test {
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static bool IsValidIdentifier(const std::string& name) {
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if (name.empty()) {
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return false;
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}
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if (!isalpha(name[0]) && name[0] != '_') {
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return false;
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}
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for (size_t i = 1; i < name.size(); ++i) {
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if (!isalnum(name[i]) && name[i] != '_') {
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return false;
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}
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}
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return true;
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}
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TEST(IR, ValidIdentifierTest) {
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Graph* g = new Graph(); // NOLINT(cppcoreguidelines-owning-memory)
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g->setName("test");
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Value* x = g->addInput();
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x->setUniqueName("x");
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x->setElemType(ONNX_NAMESPACE::TensorProto_DataType_FLOAT);
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x->setSizes({Dimension("M"), Dimension("N")});
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Node* node1 = g->create(kNeg, 1);
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node1->addInput(x);
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g->appendNode(node1);
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Value* temp1 = node1->outputs()[0];
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Node* node2 = g->create(kNeg, 1);
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node2->addInput(temp1);
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g->appendNode(node2);
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Value* y = node2->outputs()[0];
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g->registerOutput(y);
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ModelProto model;
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ExportModelProto(&model, std::shared_ptr<Graph>(g));
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for (const auto& node : model.graph().node()) {
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for (const auto& name : node.output()) {
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EXPECT_TRUE(IsValidIdentifier(name));
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}
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}
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}
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// Regression test: Tensor::elem_num() and size_from_dim() must use 64-bit
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// arithmetic. Previously, std::accumulate used `1` (int) as the initial value,
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// causing 32-bit multiplication that silently overflowed for tensors whose
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// element count exceeded INT_MAX (~2.1B). Fixed by using int64_t{1}.
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TEST(Tensor, ElemNumLargeTensorNoOverflow) {
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Tensor t;
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// 50000 * 50000 = 2,500,000,000 which exceeds INT32_MAX (2,147,483,647)
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t.sizes() = {50000, 50000};
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const int64_t expected = static_cast<int64_t>(50000) * 50000;
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EXPECT_EQ(t.elem_num(), expected);
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EXPECT_EQ(t.size_from_dim(0), expected);
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EXPECT_EQ(t.size_from_dim(1), int64_t{50000});
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}
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} // namespace Test
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} // namespace ONNX_NAMESPACE
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